feat: Vector retrieval matches tables

backend/alembic/versions/047_table_embedding.py

@@ -20,10 +20,12 @@
 def upgrade():
     # ### commands auto generated by Alembic - please adjust! ###
     op.add_column('core_table', sa.Column('embedding', sa.Text(), nullable=True))
+    op.add_column('core_datasource', sa.Column('embedding', sa.Text(), nullable=True))
     # ### end Alembic commands ###
 
 
 def downgrade():
     # ### commands auto generated by Alembic - please adjust! ###
     op.drop_column('core_table', 'embedding')
+    op.drop_column('core_datasource', 'embedding')
     # ### end Alembic commands ###

backend/apps/datasource/crud/datasource.py

@@ -15,7 +15,7 @@
 from apps.db.engine import get_engine_config, get_engine_conn
 from common.core.config import settings
 from common.core.deps import SessionDep, CurrentUser, Trans
-from common.utils.embedding_threads import run_save_table_embeddings
+from common.utils.embedding_threads import run_save_table_embeddings, run_save_ds_embeddings
 from common.utils.utils import deepcopy_ignore_extra
 from .table import get_tables_by_ds_id
 from ..crud.field import delete_field_by_ds_id, update_field
@@ -105,6 +105,8 @@ def update_ds(session: SessionDep, trans: Trans, user: CurrentUser, ds: CoreData
         setattr(record, field, value)
     session.add(record)
     session.commit()
+
+    run_save_ds_embeddings([ds.id])
     return ds
 
 
@@ -197,6 +199,7 @@ def sync_table(session: SessionDep, ds: CoreDatasource, tables: List[CoreTable])
 
     # do table embedding
     run_save_table_embeddings(id_list)
+    run_save_ds_embeddings([ds.id])
 
 
 def sync_fields(session: SessionDep, ds: CoreDatasource, table: CoreTable, fields: List[ColumnSchema]):
@@ -238,20 +241,23 @@ def update_table_and_fields(session: SessionDep, data: TableObj):
 
     # do table embedding
     run_save_table_embeddings([data.table.id])
+    run_save_ds_embeddings([data.table.ds_id])
 
 
 def updateTable(session: SessionDep, table: CoreTable):
     update_table(session, table)
 
     # do table embedding
     run_save_table_embeddings([table.id])
+    run_save_ds_embeddings([table.ds_id])
 
 
 def updateField(session: SessionDep, field: CoreField):
     update_field(session, field)
 
     # do table embedding
     run_save_table_embeddings([field.table_id])
+    run_save_ds_embeddings([field.ds_id])
 
 
 def preview(session: SessionDep, current_user: CurrentUser, id: int, data: TableObj):

backend/apps/datasource/crud/table.py

@@ -9,7 +9,7 @@
 from common.core.config import settings
 from common.core.deps import SessionDep
 from common.utils.utils import SQLBotLogUtil
-from ..models.datasource import CoreTable, CoreField
+from ..models.datasource import CoreTable, CoreField, CoreDatasource
 
 
 def delete_table_by_ds_id(session: SessionDep, id: int):
@@ -30,18 +30,24 @@ def update_table(session: SessionDep, item: CoreTable):
     session.commit()
 
 
-def run_fill_empty_table_embedding(session_maker):
+def run_fill_empty_table_and_ds_embedding(session_maker):
     try:
         if not settings.TABLE_EMBEDDING_ENABLED:
             return
 
-        SQLBotLogUtil.info('get tables')
         session = session_maker()
+
+        SQLBotLogUtil.info('get tables')
         stmt = select(CoreTable.id).where(and_(CoreTable.embedding.is_(None)))
         results = session.execute(stmt).scalars().all()
-        SQLBotLogUtil.info('result: ' + str(len(results)))
-
-        save_table_embedding(session, results)
+        SQLBotLogUtil.info('table result: ' + str(len(results)))
+        save_table_embedding(session_maker, results)
+
+        SQLBotLogUtil.info('get datasource')
+        ds_stmt = select(CoreDatasource.id).where(and_(CoreDatasource.embedding.is_(None)))
+        ds_results = session.execute(ds_stmt).scalars().all()
+        SQLBotLogUtil.info('datasource result: ' + str(len(ds_results)))
+        save_ds_embedding(session_maker, ds_results)
     except Exception:
         traceback.print_exc()
     finally:
@@ -98,3 +104,58 @@ def save_table_embedding(session_maker, ids: List[int]):
         traceback.print_exc()
     finally:
         session_maker.remove()
+
+
+def save_ds_embedding(session_maker, ids: List[int]):
+    if not settings.TABLE_EMBEDDING_ENABLED:
+        return
+
+    if not ids or len(ids) == 0:
+        return
+    try:
+        SQLBotLogUtil.info('start datasource embedding')
+        start_time = time.time()
+        model = EmbeddingModelCache.get_model()
+        session = session_maker()
+        for _id in ids:
+            schema_table = ''
+            ds = session.query(CoreDatasource).filter(CoreDatasource.id == _id).first()
+            schema_table += f"{ds.name}, {ds.description}\n"
+            tables = session.query(CoreTable).filter(CoreTable.ds_id == ds.id).all()
+            for table in tables:
+                fields = session.query(CoreField).filter(CoreField.table_id == table.id).all()
+
+                schema_table += f"# Table: {table.table_name}"
+                table_comment = ''
+                if table.custom_comment:
+                    table_comment = table.custom_comment.strip()
+                if table_comment == '':
+                    schema_table += '\n[\n'
+                else:
+                    schema_table += f", {table_comment}\n[\n"
+
+                if fields:
+                    field_list = []
+                    for field in fields:
+                        field_comment = ''
+                        if field.custom_comment:
+                            field_comment = field.custom_comment.strip()
+                        if field_comment == '':
+                            field_list.append(f"({field.field_name}:{field.field_type})")
+                        else:
+                            field_list.append(f"({field.field_name}:{field.field_type}, {field_comment})")
+                    schema_table += ",\n".join(field_list)
+                schema_table += '\n]\n'
+            # table_schema.append(schema_table)
+            emb = json.dumps(model.embed_query(schema_table))
+
+            stmt = update(CoreDatasource).where(and_(CoreDatasource.id == _id)).values(embedding=emb)
+            session.execute(stmt)
+            session.commit()
+
+        end_time = time.time()
+        SQLBotLogUtil.info('datasource embedding finished in: ' + str(end_time - start_time) + ' seconds')
+    except Exception:
+        traceback.print_exc()
+    finally:
+        session_maker.remove()

backend/apps/datasource/embedding/ds_embedding.py

@@ -1,11 +1,11 @@
 # Author: Junjun
 # Date: 2025/9/18
 import json
+import time
 import traceback
 from typing import Optional
 
 from apps.ai_model.embedding import EmbeddingModelCache
-from apps.datasource.crud.datasource import get_table_schema
 from apps.datasource.embedding.utils import cosine_similarity
 from apps.datasource.models.datasource import CoreDatasource
 from apps.system.crud.assistant import AssistantOutDs
@@ -18,42 +18,71 @@ def get_ds_embedding(session: SessionDep, current_user: CurrentUser, _ds_list, o
                      question: str,
                      current_assistant: Optional[CurrentAssistant] = None):
     _list = []
-    if current_assistant and current_assistant.type != 4:
+    if current_assistant and current_assistant.type == 1:
         if out_ds.ds_list:
             for _ds in out_ds.ds_list:
                 ds = out_ds.get_ds(_ds.id)
                 table_schema = out_ds.get_db_schema(_ds.id, question, embedding=False)
                 ds_info = f"{ds.name}, {ds.description}\n"
                 ds_schema = ds_info + table_schema
                 _list.append({"id": ds.id, "ds_schema": ds_schema, "cosine_similarity": 0.0, "ds": ds})
+
+        if _list:
+            try:
+                text = [s.get('ds_schema') for s in _list]
+
+                model = EmbeddingModelCache.get_model()
+                results = model.embed_documents(text)
+
+                q_embedding = model.embed_query(question)
+                for index in range(len(results)):
+                    item = results[index]
+                    _list[index]['cosine_similarity'] = cosine_similarity(q_embedding, item)
+
+                _list.sort(key=lambda x: x['cosine_similarity'], reverse=True)
+                # print(len(_list))
+                SQLBotLogUtil.info(json.dumps(
+                    [{"id": ele.get("id"), "name": ele.get("ds").name,
+                      "cosine_similarity": ele.get("cosine_similarity")}
+                     for ele in _list]))
+                ds = _list[0].get('ds')
+                return {"id": ds.id, "name": ds.name, "description": ds.description}
+            except Exception:
+                traceback.print_exc()
     else:
         for _ds in _ds_list:
             if _ds.get('id'):
                 ds = session.get(CoreDatasource, _ds.get('id'))
-                table_schema = get_table_schema(session, current_user, ds, question, embedding=False)
-                ds_info = f"{ds.name}, {ds.description}\n"
-                ds_schema = ds_info + table_schema
-                _list.append({"id": ds.id, "ds_schema": ds_schema, "cosine_similarity": 0.0, "ds": ds})
+                # table_schema = get_table_schema(session, current_user, ds, question, embedding=False)
+                # ds_info = f"{ds.name}, {ds.description}\n"
+                # ds_schema = ds_info + table_schema
+                _list.append({"id": ds.id, "cosine_similarity": 0.0, "ds": ds, "embedding": ds.embedding})
+
+        if _list:
+            try:
+                # text = [s.get('ds_schema') for s in _list]
+
+                model = EmbeddingModelCache.get_model()
+                start_time = time.time()
+                # results = model.embed_documents(text)
+                results = [item.get('embedding') for item in _list]
+
+                q_embedding = model.embed_query(question)
+                for index in range(len(results)):
+                    item = results[index]
+                    if item:
+                        _list[index]['cosine_similarity'] = cosine_similarity(q_embedding, item)
 
-    if _list:
-        try:
-            text = [s.get('ds_schema') for s in _list]
-
-            model = EmbeddingModelCache.get_model()
-            results = model.embed_documents(text)
-
-            q_embedding = model.embed_query(question)
-            for index in range(len(results)):
-                item = results[index]
-                _list[index]['cosine_similarity'] = cosine_similarity(q_embedding, item)
-
-            _list.sort(key=lambda x: x['cosine_similarity'], reverse=True)
-            # print(len(_list))
-            SQLBotLogUtil.info(json.dumps(
-                [{"id": ele.get("id"), "name": ele.get("ds").name, "cosine_similarity": ele.get("cosine_similarity")}
-                 for ele in _list]))
-            ds = _list[0].get('ds')
-            return {"id": ds.id, "name": ds.name, "description": ds.description}
-        except Exception:
-            traceback.print_exc()
+                _list.sort(key=lambda x: x['cosine_similarity'], reverse=True)
+                # print(len(_list))
+                end_time = time.time()
+                SQLBotLogUtil.info(str(end_time - start_time))
+                SQLBotLogUtil.info(json.dumps(
+                    [{"id": ele.get("id"), "name": ele.get("ds").name,
+                      "cosine_similarity": ele.get("cosine_similarity")}
+                     for ele in _list]))
+                ds = _list[0].get('ds')
+                return {"id": ds.id, "name": ds.name, "description": ds.description}
+            except Exception:
+                traceback.print_exc()
     return _list

backend/apps/datasource/embedding/table_embedding.py

@@ -52,7 +52,7 @@ def calc_table_embedding(tables: list[dict], question: str):
             # text = [s.get('schema_table') for s in _list]
             #
             model = EmbeddingModelCache.get_model()
-            # start_time = time.time()
+            start_time = time.time()
             # results = model.embed_documents(text)
             # end_time = time.time()
             # SQLBotLogUtil.info(str(end_time - start_time))
@@ -67,7 +67,11 @@ def calc_table_embedding(tables: list[dict], question: str):
             _list.sort(key=lambda x: x['cosine_similarity'], reverse=True)
             _list = _list[:settings.TABLE_EMBEDDING_COUNT]
             # print(len(_list))
-            SQLBotLogUtil.info(json.dumps(_list))
+            end_time = time.time()
+            SQLBotLogUtil.info(str(end_time - start_time))
+            SQLBotLogUtil.info(json.dumps([{"id": ele.get('id'), "schema_table": ele.get('schema_table'),
+                                            "cosine_similarity": ele.get('cosine_similarity')}
+                                           for ele in _list]))
             return _list
         except Exception:
             traceback.print_exc()

backend/apps/datasource/models/datasource.py

@@ -21,6 +21,7 @@ class CoreDatasource(SQLModel, table=True):
     num: str = Field(max_length=256, nullable=True)
     oid: int = Field(sa_column=Column(BigInteger()))
     table_relation: List = Field(sa_column=Column(JSONB, nullable=True))
+    embedding: str = Field(sa_column=Column(Text, nullable=True))
 
 
 class CoreTable(SQLModel, table=True):

backend/common/utils/embedding_threads.py

@@ -38,6 +38,11 @@ def run_save_table_embeddings(ids: List[int]):
     executor.submit(save_table_embedding, session_maker, ids)
 
 
-def fill_empty_table_embeddings():
-    from apps.datasource.crud.table import run_fill_empty_table_embedding
-    executor.submit(run_fill_empty_table_embedding, session_maker)
+def run_save_ds_embeddings(ids: List[int]):
+    from apps.datasource.crud.table import save_ds_embedding
+    executor.submit(save_ds_embedding, session_maker, ids)
+
+
+def fill_empty_table_and_ds_embeddings():
+    from apps.datasource.crud.table import run_fill_empty_table_and_ds_embedding
+    executor.submit(run_fill_empty_table_and_ds_embedding, session_maker)

backend/main.py

@@ -12,7 +12,7 @@
 
 from alembic import command
 from apps.api import api_router
-from common.utils.embedding_threads import fill_empty_table_embeddings
+from common.utils.embedding_threads import fill_empty_table_and_ds_embeddings
 from apps.system.crud.aimodel_manage import async_model_info
 from apps.system.crud.assistant import init_dynamic_cors
 from apps.system.middleware.auth import TokenMiddleware
@@ -36,8 +36,8 @@ def init_data_training_embedding_data():
     fill_empty_data_training_embeddings()
 
 
-def init_table_embedding():
-    fill_empty_table_embeddings()
+def init_table_and_ds_embedding():
+    fill_empty_table_and_ds_embeddings()
 
 
 @asynccontextmanager
@@ -47,7 +47,7 @@ async def lifespan(app: FastAPI):
     init_dynamic_cors(app)
     init_terminology_embedding_data()
     init_data_training_embedding_data()
-    init_table_embedding()
+    init_table_and_ds_embedding()
     SQLBotLogUtil.info("✅ SQLBot 初始化完成")
     await sqlbot_xpack.core.clean_xpack_cache()
     await async_model_info()  # 异步加密已有模型的密钥和地址